Benoît Mandelbrot, the father of Fractal Geometry, developed a multifractal model for describing price changes. Despite the commonly used models, such as the Brownian motion, the Mutifractal Model of Asset Return (MMAR) takes into account scale-consistency, long-range dependence and heavy...

Investors sometimes have strong convictions that a distinctive economic regime will prevail in the period ahead and therefore would like to form a portfolio that reflects the expected returns, standard deviations, and correlations of assets during such a regime. To do so, they typically isolate...

The paper analyses the method adopted by the index of employment protection systems developed in 1999 by the OECD and discusses its reliability and shortcomings, in particular with regards to Italy. The paper highlights a series of problems of method arising from the aggregation of the...

By utilizing the extreme dependence structure and the conditional probability of joint failure (CPJF) among risk factors, this paper characterizes a risk-stability index (RSI) that quantifies (i) common distress of risk factors, (ii) distress between specific risk factors, and (iii) distress to...

We analyze investment decisions when information is costly, with and without delegation to an agent. We use a rational-inattention model and compare it with a canonical signal-extraction model. We identify three "investment conditions". In "sour" conditions, no information is acquired and no...

The classical cobweb theorem is extended to include production lags and price forecasts. Price forecasting based on a longer period has a stabilizing effect on prices. Longer production lags do not necessarily lead to unstable prices; very long lags lead to cycles of constant amplitude. The...

We study many-to-one matchings, such as the assignment of students to colleges, where the students have preferences over the other students who would attend the same college. It is well known that the core of this model may be empty, without strong assumptions on agents' preferences. We...

We study the properties of generalized stochastic gradient (GSG) learning in forward-looking models. We examine how the conditions for stability of standard stochastic gradient (SG) learning both differ from and are related to E-stability, which governs stability under least squares learning. SG...

We consider optimal stopping problems in uncertain environments for an agent assessing utility by virtue of dynamic variational preferences or, equivalently, assessing risk by dynamic convex risk measures. The solution is achieved by generalizing the approach in terms of multiple priors...

We consider long-run behavior of agents assessing risk in terms of dynamic convex risk measures or, equivalently, utility in terms of dynamic variational preferences in an uncertain setting. By virtue of a robust representation, we show that all uncertainty is revealed in the limit and agents...